From the following example, the most important methodological challenge while conducting a cohort study is:
D. Subjects do not get randomized in a simple cohort study. Hence there is no question of allocation concealment. When valid instruments and a reasonable follow-up schedule are used, identification of those who develop the ‘event’ of interest/outcome is often not difficult in a cohort design. Often the most difficult part is to identify a reasonable control cohort that lacks the ‘exposure’ of interest. Internal controls refer to those who are ‘non-exposed’ but derived from the same study population as the ‘exposed’. External control refers to an independently recruited cohort without the exposure.
Reference:
In a study investigating the mean cholesterol levels in 36 patients taking olanzapine, the mean was found to be 262 mg/dL. The standard deviation of this observation was 15 mg/dL.
The 95% confidence interval for this observation is are:
D. 95% confidence limits of means of a sample are nothing but the range between an observation less than approximately two standard error units less than mean value and an observation two standard error units more than the mean value. Using mathematical expression, 95% confidence limits = mean ± (2 × standard error of mean).
Standard error of mean is calculated as SE = standard deviation/√sample size.
SE = 15/√36 = 15/6 = 2.5 in this question.
Hence 95% confidence limits are
262 ± (2 × 2.5) = 262 ± 5 = 257, 267.
In a normal distribution curve, 99% of observations will fall within which of the following values of standard deviation (SD)?
B. An important property of the normal distribution curve is the relationship between the SD of normally distributed observations and probability. Normal distribution curves are symmetric and bell-shaped. Nearly 68.5% of the sampled population will lie within 1 SD of the mean on either side of the curve, 95.5% within 2 SDs, and 99% within 3 SDs. In other words, there is a 1% chance that an observation will fall outside +3 SD to –3 SD; a 5% chance that it will fall outside +2SD to –2SD and nearly 30% chance that it will occur outside +1SD and –1SD.
Confidence intervals are used to describe the range of uncertainty around the estimated value of an outcome from the sample studied.
Which of the following statements about confidence intervals is incorrect?
C. If the confidence interval includes a null treatment effect, the null hypothesis cannot be rejected within the set levels of confidence limits. Confidence intervals provide a measure of dispersion of the point estimate within stipulated confidence limits (arbitrarily 95% corresponds to a p value of 5%). In other words, confidence intervals provide the assured range within which the true value may lie. Confidence intervals are a measure of precision of the results obtained from a study. The larger the sample studied, the narrower the intervals. If the confidence intervals cross the value ‘0’ for the difference between means then the results are statistically not significant. If it crosses the value ‘1’ for ratio measures such as the odds ratio, it is not significant. If it crosses infinity for inverse ratios such as NNT then it is not significant.
A clinical researcher is examining the incidence of akathisia in two groups of patients. One group (n = 35) has been prescribed benzodiazepine for use as required while the other group (n = 35) is free from any benzodiazepine exposure. The outcome is measured as proportion of patients who develop akathisia in a dichotomous scale. Akathisia develops in 10 patients without benzodiazepines and in 20 patients with benzodiazepines.
Which of the following statistical tests is best suited to analyze the statistical significance of the difference between the two groups?
A. In this study, the dependent variable is treated as a categorical outcome. In other words, the population has been categorized into ‘akathisia present’ or ‘akathisia absent’. This type of outcome yields frequency counts or proportions that can be analyzed for significance using the chi square test. The t test is used for comparing means. The Wilcoxon rank sum test is a non-parametric equivalent of the t test. Pearson coefficients are used to analyze correlation. Regression analysis are used to predict one variable from another when they are correlated.
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